JMIR Mental Health (Mar 2022)

Longitudinal Relationships Between Depressive Symptom Severity and Phone-Measured Mobility: Dynamic Structural Equation Modeling Study

  • Yuezhou Zhang,
  • Amos A Folarin,
  • Shaoxiong Sun,
  • Nicholas Cummins,
  • Srinivasan Vairavan,
  • Rebecca Bendayan,
  • Yatharth Ranjan,
  • Zulqarnain Rashid,
  • Pauline Conde,
  • Callum Stewart,
  • Petroula Laiou,
  • Heet Sankesara,
  • Faith Matcham,
  • Katie M White,
  • Carolin Oetzmann,
  • Alina Ivan,
  • Femke Lamers,
  • Sara Siddi,
  • Elisabet Vilella,
  • Sara Simblett,
  • Aki Rintala,
  • Stuart Bruce,
  • David C Mohr,
  • Inez Myin-Germeys,
  • Til Wykes,
  • Josep Maria Haro,
  • Brenda WJH Penninx,
  • Vaibhav A Narayan,
  • Peter Annas,
  • Matthew Hotopf,
  • Richard JB Dobson

DOI
https://doi.org/10.2196/34898
Journal volume & issue
Vol. 9, no. 3
p. e34898

Abstract

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BackgroundThe mobility of an individual measured by phone-collected location data has been found to be associated with depression; however, the longitudinal relationships (the temporal direction of relationships) between depressive symptom severity and phone-measured mobility have yet to be fully explored. ObjectiveWe aimed to explore the relationships and the direction of the relationships between depressive symptom severity and phone-measured mobility over time. MethodsData used in this paper came from a major EU program, called the Remote Assessment of Disease and Relapse–Major Depressive Disorder, which was conducted in 3 European countries. Depressive symptom severity was measured with the 8-item Patient Health Questionnaire (PHQ-8) through mobile phones every 2 weeks. Participants’ location data were recorded by GPS and network sensors in mobile phones every 10 minutes, and 11 mobility features were extracted from location data for the 2 weeks prior to the PHQ-8 assessment. Dynamic structural equation modeling was used to explore the longitudinal relationships between depressive symptom severity and phone-measured mobility. ResultsThis study included 2341 PHQ-8 records and corresponding phone-collected location data from 290 participants (age: median 50.0 IQR 34.0, 59.0) years; of whom 215 (74.1%) were female, and 149 (51.4%) were employed. Significant negative correlations were found between depressive symptom severity and phone-measured mobility, and these correlations were more significant at the within-individual level than the between-individual level. For the direction of relationships over time, Homestay (time at home) (φ=0.09, P=.01), Location Entropy (time distribution on different locations) (φ=−0.04, P=.02), and Residential Location Count (reflecting traveling) (φ=0.05, P=.02) were significantly correlated with the subsequent changes in the PHQ-8 score, while changes in the PHQ-8 score significantly affected (φ=−0.07, P<.001) the subsequent periodicity of mobility. ConclusionsSeveral phone-derived mobility features have the potential to predict future depression, which may provide support for future clinical applications, relapse prevention, and remote mental health monitoring practices in real-world settings.